How to use a radiation monitor to reduce LISA noise levelsHow to use a radiation monitor to reduce LISA noise levelsDiana Shaul1, Henrique Araújo1, Daniel Hollington1, Alberto Lobo2, Markus Schulte1, Tim Sumner1, Simon Waschke1, Peter Wass3

1 Imperial College London; 2ICE/CSIC and IEEC; 3University of Trento

High energy cosmic ray and solar particle fluxes will charge up the LISA test masses (TMs). This charge will result in spurious electromagnetic forces acting on the TMs, disturbing their geodesic motion. The primary approach to minimise the impact of these forces is to discharge the TMs using the photoelectric effect. Unfortunately, the flux and energy spectrum of these high energy particles varies over time and therefore it is not easy to match charging and discharging rates, which would minimise the disturbances induced by charging. The gravitational reference sensor (GRS) can be used to measure the average charge accumulated, but not the shorter term variations in the charging rate. A radiation monitor (RM) can enable tracking of these changes. 

We describe how a RM could be used to reduce the charging disturbances for LISA and the plans for use of the RM on LISA Pathfinder (LPF), including an approach that could enable acceleration noise associated with charging to be effectively subtracted.

1. INTRODUCTION1. INTRODUCTION1.1 Charging Disturbances• Charge on the TM leads to Coulomb and Lorentz forces from interactions with

GRS conducting surfaces and IMF, respectively. • These forces give rise to different types of disturbance:

1. Acceleration noise, due to fluctuations in e.g. voltage [1]2. Modification of the effective stiffness describing TM-S/C coupling, due

to position dependence of Coulomb forces [1]3. Coherent Fourier components, due to time dependence of the amount of

charge on the TM [2,3]

1.2 The Incident Flux• TM charging characteristics (net charging rate and charging shot noise)

depend on the incident particle flux and its energy spectrum [4]• Higher energy particles => higher charge multiplicity events => more noise

and higher net charging rates, compared with lower energy particles [4]• Solar Energetic Particle (SEP) energy spectra are softer than Galactic

Cosmic Ray (GCR) spectra => A given particle flux will result in different TM charging characteristics, dependent on the proportion of SEP and GCR particles. [4]

• The charging disturbances will also depend on the variability of the incident flux over time. This may give rise to sharp or gradual changes or periodicities in the charging rate, potentially resulting in spectral leakage, modulation of the coherent Fourier components and the masking of true signals in the LISA bandwidth.

•  Variations in flux:• Solar Cycle: 11 year period; 50% difference in charging rate between solar

minimum and maximum [4, 5]; Gradual and sharp changes possible [6]• Solar rotation: ~ 27 day period; ~ 1 – 5 % GCR flux modulation [6]• Jovian synodic year: 13 months; <5% TM charging rate modulation [7]• SEPs: ~ 1 day–1 week; ~100-70000% (rare) TM charging rate increase [4]• Forbush Decreases: ~days; ~ few – 35% GCR flux modulation. [6]• Other GCR modulations: ~<few% in ~mins – week [8, 9]; Periodic

fluctuations(?) [7, 10]

1.3 Charge Management1. Charge measurement: Apply dither voltages to opposing electrodes and

measure resultant TM displacement => average charging rate. Accuracy depends on the dither voltage amplitude, dither frequency, degree of freedom, and integration time. Typically, an accuracy of 104e is reached in ~1 hour. This measurement does not give information on the charging shot noise nor the short term variability in the average charging rate.

2. TM Discharge: Use UV light to discharge via the photoelectric effect. Nominal science mode: closed loop control to match charging and discharging rates as closely as possible, to minimise disturbances. [11]

2. THE RADIATION MONITOR2. THE RADIATION MONITOR2.1 Aims• Independent monitor of incident particle fluxes• Minimise/track disturbances due to charging • Help to manage disturbances • Match charging/discharging rates• Identify “DC” changes/coherent Fourier components• Subtract Fourier components and charging noise

2.2 LPF RM Design(see e.g. [12] for more details)

• Shielding to mimic TM shielding• Telescopic arrangement to enable SEP and GCR spectral discrimination

within ~1hr for events registering in both diodes• Minimum isotropic count rate >7c/s, set to ensure: recognise small changes

in flux associated with e.g. SEPs; RM shot noise ~ TM charging shot noise; detect periodic modulation in flux before exceeds LISA noise

• Maximum count rate: large SEP: ~1500 c/s (isotropic), ~ 100 (coincident)• Nominal time bin counter <30s (LPF: 1 mHz ≤ f ≤ 30 mHz)

References:

2 Silicon PIN diodes in telescopic arrangement,

Data : Coincidence spectrum, 10 mins

integrationSingles rates, 10 secs

integration

2.3 Minimum Aims for RM on LPF• Establish Monte Carlo (GEANT [4, 5, 12], FLUKA [13, 14, 15]) TM and RM

charging simulation accuracy• Establish approximate GCR and SEP transfer functions between RM and TM

charge• Establish/limit PSD of GCR flux and investigate whether there are any

periodicities in the GCR flux in the LISA frequency band.• Establish the SEP flux enhancements distributions (temporal and fluence)

seen by RM• Demonstrate the closed loop charge control process and estimate gain factor

2.4 Additional Aim for LISA: Derive TM charging rate and shot noise using RM

• Accurate measurement of RM-TM transfer function for net charging rate and charging noise could enable not only the coherent Fourier components but also charging shot noise to be effectively subtracted from the science data, as the RM would enable their independent and continuous measurement.

• This is an ambitious aim as there is a high level of ambiguity in the transfer function measurement. This is because it must be calibrated using the 2 direct measurements of the TM charging rate and shot noise, compared with the RM singles rate and the multi-channel coincidence deposited energy spectrum.

• To break the degeneracy, multiple measurements are needed in as diverse solar conditions as possible. On LPF, there is no real-time feedback between RM and GRS and hence this calibration may be limited due to the difficulty in predicting when a SEP will occur. However it should be possible for LISA.

2.4.1 Steps• Start with a RM-TM transfer function derived from Monte Carlo models• Recalibrate RM-TM transfer function in flight based on direct TM charging

rate/noise measurements• Ambiguity => iterate with each new direct TM measurement

2.4.2 Direct measurement: TM charging rate, shot noise• The TM charging rate and shot noise may both be measured by applying a

dither voltage to opposing electrodes and measuring the resultant TM displacement. [16]

2.5 RM improvements for LISA• Electron monitor to track flux changes due to Jovian flux/early SEP warning• Multiple, distributed RMs on LISA S/C to a/c for anisotropies in flux during

SEP events, Forbush decreases etc..• Real-time, on-board feedback between RM and GRS to: calibrate RM; match

charging and discharging rates; to benefit from early SEP warning• Improved spectral discrimination

1. Measurements = Synchronised GRS TM charging rate (noise) measurement with UV lamps off and acquisition of RM coincidence spectra

2. Scale the RM coincidence spectrum using the average RM singles rate over the same period.

3. Split the RM to TM charging noise transformation matrix into n segments, where n is the total number of direct TM charging rate (noise) measurements. The optimum positions of the segments will be derived using MC models.

4. Introduce n coefficients in the transformation matrix and solve for these coefficients, using the scaled coincidence spectra and direct TM charging measurements.

5. Repeat each time another suitable TM charging measurement is made to iteratively improve the transformation matrix.

6. To optimally improve this matrix, measurements should be made in as different solar conditions as possible.

Schematic illustrating calibration of RM-TM transfer function

N.B. It still needs to be confirmed whether the LPF RM spectral resolution is sufficient to distinguish variations in GCR spectrum

during mission lifetime.

Accuracy of measurement (e/s)

Minimum integration

time (hours)

Maximum integration

time (hours) Effective charging

rate (noise)

Net charging

rate GCR, solar

quiet 0.6 0.1 4 24x14

Small SEP 10 10 1 5 Large SEP 5000 5000 1 7

Small Forbush

Decrease or similar GCR

decrease

1.5 0.1 3.5 4

Large Forbush Decrease

10.5 1 0.1 24

Solar Rotation

0.3 0.03 24x3.5 24x13

Example measurement accuracy for 1 day

integration and dither voltage of 1V

Rough guide to LPF requirements for sensitivity and integration time for

direct TM measurements in different solar conditions

[9] Quenby J., et al., JGR, in publication (2008)[10] Starodubtsev et al., Ann. Geophys 24, 779 (2006).[11] Shaul DNA et al., International Journal of Modern Physics D, in publication (2008).[12] Wass PJ, PhD thesis (2007).[13] Vocca, H., et al., Class. Quantum Grav. 22, S319 (2005).[14] Vocca, H., et al., Class. Quantum Grav. 21, S665 (2004).[15] Grimani, C. et al., Class. Quantum Grav. 22, S327 (2005).[16] Weber, W., Private Communication (2007).

[1] Shaul DNA et al., Class. Quantum Grav. 22, S297 (2005).[2] Shaul DNA et al., International Journal of Modern Physics D 14, 51 (2005).[3] Shaul DNA et al., Class. Quantum Grav. 21, S647 (2004).[4] Araújo HM et al., Astroparticle Physics 22, 451 (2005).[5] Wass PJ et al., Class. Quantum Grav. 22, S311 (2005).[6] Jursa AS (ed.), Handbook of geophysics and the space environment, 4th edn., Air Force Geophysics Laboratory (1985).[7] Shaul DNA et al., 6th International LISA Symposium, AIP Conf. Proc. 873, 172 (2006).[8] Blake JB et al., in preparation (2008).